A method for determining a lowest stimulation threshold current level in a group of channels of a neuromonitoring device. The method includes stimulating tissue at a current level from a predetermined range of current levels as a sequence of pulses delivered at a frequency. The stimulating includes increasing the current level of each pulse in the sequence of pulses from an immediately preceding pulse by a first current increment. The method includes determining that a first evocation pulse from the sequence of pulses evokes a first muscular response. The method includes stimulating the tissue with a second evocation pulse from the sequence of pulses to evoke a second muscular response. The stimulating includes decreasing the frequency of the delivery of each pulse in the sequence of pulses and increasing the current level of each pulse in the sequence of pulses from the immediately preceding pulse by a second current increment. The method includes determining that the second evocation pulse from the sequence of pulses evokes the second muscular response.

A wearable biofluid volume and composition system includes a microfluidic flexible fluid capture substrate having a microfluidic channel configured as a sweat collection channel and is configured to be worn on a human body and to collect and analyze biofluid. The microfluidic flexible fluid capture substrate further has a plurality of conductive traces and electrodes. An electronic module is attached to the microfluidic flexible fluid capture substrate and is configured to measure and analyze data from the biofluid collected by the microfluidic flexible fluid capture substrate and to transmit the analyzed data to a smart device.

The present invention relates to a physiological monitor and system, more particularly to an electroencephalogram (EEG) monitor and system, and a method of detecting the presence or occurrence of suppression in the EEG signal. Accurately detecting signal suppression in real-time provides the clinician with the ability to prevent possibly severe, long-term damage to patients as a result of excessive anesthetic or sedative. The present invention provides such a system and method for accurately and automatically detecting suppression in physiological, particularly EEG, signals in real-time and allowing for the administration of treatment or medication to reverse the effects of such situations, or minimize the harm caused. The present invention also allows for the use of closed-loop treatment or drug delivery systems to further automate the process and provide rapid treatment to a patient to reverse or minimize potential harm.

According to an embodiment, a bed system includes a plurality of bed devices and a first input/output device capable of communicating with the plurality of bed devices. The first input/output device implements a first operation. During the first operation, the first input/output device receives input of a first set value relating to a first item set in each of the plurality of bed devices. At least one of the first input/output device and the plurality of bed devices implements an operation corresponding to the first set value. Thus, a bed system having improved usability is provided.

The present disclosure provides a method, performed in an accessory device, for communicating a leakage state of an ostomy appliance, wherein the accessory device comprises an interface configured to communicate with one or more devices of an ostomy system, the one or more devices comprising a monitor device, and/or the ostomy appliance configured to be placed on a skin surface of a user. The method comprises obtaining monitor data from the one or more devices, the monitor data being indicative of presence of fluid at a proximal side of a first adhesive layer of the ostomy appliance towards the skin surface; determining a leakage state at the proximal side of the first adhesive layer of the ostomy appliance based on the monitor data, and communicating the leakage state of the ostomy appliance via the interface.

An apparatus for non-invasively estimating blood pressure is provided. Thee apparatus for estimating blood pressure may include a bio-signal measurer configured to measure a bio-signal from a user and a processor configured to estimate blood pressure using the measured bio-signal. The processor may extract a first feature and a second feature from the bio-signal at an extraction time, estimate changes in the first feature and the second feature which have occurred during a time period from a calibration time at which the first feature and the second feature are calibrated to the extraction time at which the first feature and the second feature are extracted, and estimate a blood pressure based on the changes in the first feature and the second feature.

Described herein are assistant robots that anticipate needs of one or more people (or animals). The assistant robots may recognize a current activity, knowledge of the person's routines, and contextual information. As such, the assistant robots can provide or offer to provide appropriate robotic assistance. The assistant robots can learn users' habits or be provided with knowledge regarding humans in its environment. The assistant robots develop a schedule and contextual understanding of the persons' behavior and needs. The assistant robots may interact, understand, and communicate with people before, during, or after providing assistance. The robot can combine gesture, clothing, emotional aspect, time, pose recognition, action recognition, and other observational data to understand people's medical condition, current activity, and future intended activities and intents.

Systems, instruments, and methods for surgical navigation with verification feedback are provided. The systems, instruments, and methods may be used to verify a trajectory of a surgical tool during a procedure. The systems, instruments, and methods may receive one or more captured images of an anatomical portion of a patient; execute a surgical plan to insert the surgical tool into the anatomical portion; receive sensor data collected from one or more sensors being inserted into the anatomical portion; determine whether the sensor data corresponds to the surgical plan; and send, in response to determining that the sensor data does not correspond to the surgical plan, an alert indicating that the surgical tool is not being inserted according to the surgical plan. The one or more sensors may be attached to the surgical tool.

Systems and methods for monitoring acute:chronic workload ratio (ACWR) are described. An indicator of workload is received from a device worn or carried by a user. An acute workload is determined for the user based on the received indicator of workload over a first period of time. A chronic workload is determined for the user based on the received indicator of workload over a second period of time, where the first period of time is shorter than the second period of time. A current ACWR is determined for the user based on the acute workload and the chronic workload.

A system may obtain a set of features characterizing a segment of inertial measurement unit (IMU) data generated by an IMU of an ear-wearable device. The system may apply a machine learning model (MLM) that takes the features characterizing the segment of the IMU data as input. The system may determine, based on output values produced by the MLM, whether a user of the ear-wearable device has potentially been subject to physical abuse. The system may then perform an action in response to determining that the user of the ear-wearable device has potentially been subject to physical abuse.